diff --git a/SECURITY.md b/SECURITY.md
index c9f460f0db..f0e7e8c179 100644
--- a/SECURITY.md
+++ b/SECURITY.md
@@ -4,7 +4,7 @@
 
 | Version | Supported          |
 |---------| ------------------ |
-| 0.9.0   | :white_check_mark: |
+| 0.10.0   | :white_check_mark: |
 
 
 ## How we do security
@@ -44,6 +44,7 @@ TorchServe as much as possible relies on automated tools to do security scanning
         - Encoding: Convert special characters into safe representations.
         - Verification: Run tooling that identifies potential script injections (e.g. [models that detect prompt injection attempts](https://python.langchain.com/docs/guides/safety/hugging_face_prompt_injection)).
 7. If you intend to run multiple models in parallel with shared memory, it is your responsibility to ensure the models do not interact or access each other's data. The primary areas of concern are tenant isolation, resource allocation, model sharing and hardware attacks.
+8. TorchServe supports token authorization: check [documentation](https://github.com/pytorch/serve/blob/master/docs/token_authorization_api.md) for more information. 
 
 
 
diff --git a/docs/Security.md b/docs/Security.md
deleted file mode 100644
index 7723088b24..0000000000
--- a/docs/Security.md
+++ /dev/null
@@ -1,47 +0,0 @@
-# Security Policy
-
-## Supported Versions
-
-| Version | Supported          |
-|---------| ------------------ |
-| 0.9.0   | :white_check_mark: |
-| 0.10.0  | :white_check_mark: |
-
-
-## How we do security
-
-TorchServe as much as possible relies on automated tools to do security scanning, in particular we support
-1. Dependency Analysis: Using Dependabot
-2. Docker Scanning: Using Snyk
-3. Code Analysis: Using CodeQL
-
-## Important Security Guidelines
-
-1. TorchServe listens on the following ports
-    1. HTTP - `8080`, `8081`, `8082`
-    2. gRPC - `7070`, `7071`
-
-    These ports are accessible to `localhost` by default.  The address can be configured by following the [guide](https://pytorch.org/serve/configuration.html#configure-torchserve-listening-address-and-port)
-    TorchServe does not prevent users from configuring the address to be `0.0.0.0`. Please be aware of the security risks if you use `0.0.0.0`
-2. TorchServe's Docker image is configured to expose the ports `8080`, `8081`, `8082`, `7070`, `7071` to the host by [default](https://github.com/pytorch/serve/blob/master/docker/Dockerfile). When these ports are mapped to the host, make sure to use `localhost` or a specific ip address.
-
-3. Be sure to validate the authenticity of the `.mar` file being used with TorchServe.
-    1. A `.mar` file being downloaded from the internet from an untrustworthy source may have malicious code, compromising the integrity of your application
-    2. TorchServe executes arbitrary python code packaged in the `mar` file. Make sure that you've either audited that the code you're using is safe and/or is from a source that you trust
-4. By default TorchServe allows you to register models from all URLs. Make sure to set `allowed_urls` parameter in config.properties to restrict this. You can find more details in the [configuration guide](https://pytorch.org/serve/configuration.html#other-properties)
-    - `use_env_allowed_urls=true` is required in config.properties to read `allowed_urls` from environment variable
-5. Enable SSL:
-
-    TorchServe supports two ways to configure SSL:
-    1. Using a keystore
-    2. Using private-key/certificate files
-
-    You can find more details in the [configuration guide](https://pytorch.org/serve/configuration.html#enable-ssl)
-6. TorchServe supports token authorization: check [documentation](https://github.com/pytorch/serve/blob/master/docs/token_authorization_api.md) for more information. 
-
-
-
-
-## Reporting a Vulnerability
-
-If you find a serious vulnerability please report it to opensource@meta.com and torchserve@amazon.com